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Leibniz international proceedings in informatics

Linear Time Algorithm for Quantum 2SAT

Itai Arad, Miklós Sántha, Aarthi Sundaram, Shengyu Zhang

Published Jan 1, 2016• 1 citation
Publisher

Abstract

A canonical result about satisfiability theory is that the 2-SAT problem can be solved in linear time, despite the NP-hardness of the 3-SAT problem. In the quantum 2-SAT problem, we are given a family of 2-qubit projectors Q_{ij} on a system of n qubits, and the task is to decide whether the Hamiltonian H = sum Q_{ij} has a 0-eigenvalue, or it is larger than 1/n^c for some c = O(1). The problem is not only a natural extension of the classical 2-SAT problem to the quantum case, but is also equivalent to the problem of finding the ground state of 2-local frustration-free Hamiltonians of spin 1/2, a well-studied model believed to capture certain key properties in modern condensed matter physics. While Bravyi has shown that the quantum 2-SAT problem has a classical polynomial-time algorithm, the running time of his algorithm is O(n^4). In this paper we give a classical algorithm with linear running time in the number of local projectors, therefore achieving the best possible complexity.

DOI
10.4230/lipics.icalp.2016.15

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A canonical result about satisfiability theory is that the 2-SAT problem can be solved in linear time, despite the NP-hardness of the 3-SAT problem. In the quantum 2-SAT problem, we are given a family of 2-qubit projectors $Π_{ij}$ on a system of $n$ qubits, and the task is to decide whether the Hamiltonian $H=\sum Π_{ij}$ has a 0-eigenvalue, or it is larger than $1/n^α$ for some $α=O(1)$. The problem is not only a natural extension of the classical 2-SAT problem to the quantum case, but is also equivalent to the problem of finding the ground state of 2-local frustration-free Hamiltonians of spin $\frac{1}{2}$, a well-studied model believed to capture certain key properties in modern condensed matter physics. While Bravyi has shown that the quantum 2-SAT problem has a classical polynomial-time algorithm, the running time of his algorithm is $O(n^4)$. In this paper we give a classical algorithm with linear running time in the number of local projectors, therefore achieving the best possible complexity.

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A canonical result about satisfiability theory is that the 2-SAT problem can be solved in linear time, despite the NP-hardness of the 3-SAT problem. In the quantum 2-SAT problem, we are given a family of 2-qubit projectors Q_{ij} on a system of n qubits, and the task is to decide whether the Hamiltonian H = sum Q_{ij} has a 0-eigenvalue, or it is larger than 1/n^c for some c = O(1). The problem is not only a natural extension of the classical 2-SAT problem to the quantum case, but is also equivalent to the problem of finding the ground state of 2-local frustration-free Hamiltonians of spin 1/2, a well-studied model believed to capture certain key properties in modern condensed matter physics. While Bravyi has shown that the quantum 2-SAT problem has a classical polynomial-time algorithm, the running time of his algorithm is O(n^4). In this paper we give a classical algorithm with linear running time in the number of local projectors, therefore achieving the best possible complexity.
A canonical result about satisfiability theory is that the 2-SAT problem can be solved in linear time, despite the NP-hardness of the 3-SAT problem. In the quantum 2-SAT problem, we are given a family of 2-qubit projectors ΠijΠ_{ij}Πij​ on a system of nnn qubits, and the task is to decide whether the Hamiltonian H=∑ΠijH=\sum Π_{ij}H=∑Πij​ has a 0-eigenvalue, or it is larger than 1/nα1/n^α1/nα for some α=O(1)α=O(1)α=O(1). The problem is not only a natural extension of the classical 2-SAT problem to the quantum case, but is also equivalent to the problem of finding the ground state of 2-local frustration-free Hamiltonians of spin 12\frac{1}{2}21​, a well-studied model believed to capture certain key properties in modern condensed matter physics. While Bravyi has shown that the quantum 2-SAT problem has a classical polynomial-time algorithm, the running time of his algorithm is O(n4)O(n^4)O(n4). In this paper we give a classical algorithm with linear running time in the number of local projectors, therefore achieving the best possible complexity.
A well-known result about satisfiability theory is that the 2-SAT problem can be solved in linear time, despite the NP-hardness of the 3-SAT problem. In the quantum 2-SAT problem, we are given a family of 2-qubit projectors Πij\Pi_{ij}Πij​ on a system of nnn qubits, and the task is to decide whether the Hamiltonian H=∑ΠijH=\sum \Pi_{ij}H=∑Πij​ has a 0-eigenvalue, or all eigenvalues are greater than 1/nα1/n^\alpha1/nα for some α=O(1)\alpha=O(1)α=O(1). The problem is not only a natural extension of the classical 2-SAT problem to the quantum case, but is also equivalent to the problem of finding a ground state of 2-local frustration-free Hamiltonians of spin 12\frac{1}{2}21​, a well-studied model believed to capture certain key properties in modern condensed matter physics. Bravyi has shown that the quantum 2-SAT problem has a deterministic algorithm of complexity O(n4)O(n^4)O(n4) in the algebraic model of computation where every arithmetic operation on complex numbers can be performed in unit time, and nnn is the number of variables. In this paper we give a deterministic algorithm in the algebraic model with running time O(n+m)O(n+m)O(n+m), where mmm is the number of local projectors, therefore achieving the best possible complexity in that model. We also show that if in the input every number has a constant size representation then the bit complexity of our algorithm is O((n+m)M(n))O((n+m) M(n))O((n+m)M(n)), where M(n)M(n)M(n) denotes the complexity of multiplying two nnn-bit integers. A conference version of this paper appeared in the Proceedings of the 43rd International Colloquium on Automata, Languages and Programming (ICALP'16), 2016.
The Boolean constraint satisfaction problem 3-SAT is arguably the canonical NP-complete problem. In contrast, 2-SAT can not only be decided in polynomial time, but in fact in deterministic linear time. In 2006, Bravyi proposed a physically motivated generalization of k-SAT to the quantum setting, defining the problem "quantum k-SAT". He showed that quantum 2-SAT is also solvable in polynomial time on a classical computer, in particular in deterministic time O(n^4), assuming unit-cost arithmetic over a field extension of the rational numbers, where n is number of variables. In this paper, we present an algorithm for quantum 2-SAT which runs in linear time, i.e. deterministic time O(n+m) for n and m the number of variables and clauses, respectively. Our approach exploits the transfer matrix techniques of Laumann et al. [QIC, 2010] used in the study of phase transitions for random quantum 2-SAT, and bears similarities with both the linear time 2-SAT algorithms of Even, Itai, and Shamir (based on backtracking) [SICOMP, 1976] and Aspvall, Plass, and Tarjan (based on strongly connected components) [IPL, 1979].
The local Hamiltonian problem is the canonical QMA\mathsf{QMA}QMA-complete problem, and O(2n)O(2^n)O(2n) time classical algorithms and O(2n/2)O(2^{n/2})O(2n/2) time quantum algorithms are known to solve the problem in the worst case. It is not clear how to improve these brute force strategies for a broad class of the problem because ground states are highly entangled in general, and we cannot directly apply known strategies for classical CSPs. In this work, we present exponentially faster classical and quantum algorithms under two mild assumptions: (1) the Hamiltonian is frustration-free on YES instances, and (2) it is approximately regular, meaning that every qubit is acted upon by approximately the same number of constraints. We complement these upper bounds by showing that, assuming (Q)SETH, quantum 5-SAT admits no non-trivial worst-case speedup. Our lower bound further demonstrates that the dependence of our algorithms on regularity is in some sense nearly optimal. Specifically, quantum 5-SAT remains (Q)SETH-hard even for Hamiltonians in which all but O(n)O(\sqrt{n})O(n​) qubits participate in only constantly many constraints, while the remaining O(n)O(\sqrt{n})O(n​) qubits each participate in O(n)O(\sqrt{n})O(n​) constraints. By contrast, if either the size of this high-degree subset or the degrees of its qubits is reduced by a factor of nδn^δnδ, for any δ>0δ>0δ>0, our algorithm solves the problem in time O(2(1−ε)n)O(2^{(1- \varepsilon)n})O(2(1−ε)n) for some ε>0\varepsilon>0ε>0. Together, our upper and lower bounds establish a fine-grained complexity dichotomy for quantum satisfiability.
The Quantum k-SAT problem is the quantum generalization of the k-SAT problem. It is the problem whether a given local Hamiltonian is frustration-free. Frustration-free means that the ground state of the k-local Hamiltonian minimizes the energy of every local interaction term simultaneously. This is a central question in quantum physics and a canonical QMA_1-complete problem. The Quantum k-SAT problem is not as well studied as the classical k-SAT problem in terms of special tractable cases, approximation algorithms and parameterized complexity. In this paper, we will give a graph-theoretic study of the Quantum k-SAT problem with the structures core and radius. These hypergraph structures are important to solve the Quantum k-SAT problem. We can solve a Quantum k-SAT instance in polynomial time if the derived hypergraph has a core of size n-m+a, where a is a constant, and the radius is at most logarithmic. If it exists, we can find a core of size n-m+a with the best possible radius in polynomial time, whereas finding a general minimum core with minimal radius is NP-hard.
We introduce the fermionic satisfiability problem, Fermionic k -SAT: this is the problem of deciding whether there is a fermionic state in the null-space of a collection of fermionic, parity-conserving, projectors on n fermionic modes, where each fermionic projector involves at most k fermionic modes. We prove that this problem can be solved efficiently classically for k = 2 . In addition, we show that deciding whether there exists a satisfying assignment with a given fixed particle number parity can also be done efficiently classically for Fermionic 2-SAT: this problem is a quantum-fermionic extension of asking whether a classical 2-SAT problem has a solution with a given Hamming weight parity. We also prove that deciding whether there exists a satisfying assignment for particle-number-conserving Fermionic 2-SAT for some given particle number is NP-complete. Complementary to this, we show that Fermionic 9-SAT is QMA 1 -hard.